As demand on specification requirements of semiconductor devices continue to increase, so too will the demand on improved measurement and analysis techniques used to quantify characteristics of semiconductor wafers. In many semiconductor fabrication and processing settings one or more thin films may be deposited onto a semiconductor wafer surface. For instance, thin films may include oxide, nitride, and/or metal layers, among others. Characteristics such as the thickness and composition of each thin film must be tightly controlled during the manufacturing process to ensure proper performance of the resulting semiconductor devices.
Previously, continuous film approximation (CFA) methods have been implemented in order to determine the relative percentage of multiple components of a thin film. For instance, one commonly implemented CFA method includes the Bruggeman effective medium approximation (BEMA). The BEMA model treats a set of components of a given thin film as an alloy. In this regard, the nonlinear BEMA model treats the components of a thin film as though they are mixed perfectly. For example, in the case of HfSiON thin films, a four-component BEMA model may treat Si, SiO2, HfO2, and SiN as four components of the thin film. In turn, the fraction of HfO2 may be correlated to the percentage of hafnium in the film, while the fraction of SiN may be correlated to the nitrogen percentage in the film.
The prior methods consist of a top-down approach, whereby optical dispersion data for the various individual BEMA components (e.g., Si, SiO2, HfO2, and SiN in the case of a 4-component BEMA model for HfSiON) are used to simulate the thin film as a whole. This top-down approach does not provide sufficient detail for the given thin film (e.g., HfSiON). For instance, the prior methods do not provide sufficient measurement performance of the thickness, and relative amount of the components of the film (e.g., Hf percentage or N percentage). As such, it would be desirable to provide a method and system, which cures the deficiencies of the prior art, thereby improving measurement performance (e.g., precision, repeatability, and stability) of the thickness and composition of a given thin film utilizing optical dispersion modeling.